AI assistants and automation that work from your own data
Answers your team can trust, drawn from your own documents, with a person kept in the loop.
Use case · A home-appliance brand selling online
The support desk that stopped drowning
A composite of the projects we take on: the problem, what we built, and what changed. Pick an act to jump the film to it.
Who it is for
Is this you?
- Support teams answering the same questions every day
- Operations teams copying data between tools by hand
- Companies with policies, manuals and records nobody can search
What you get
- Knowledge base built from your documents and databases
- Chat or email assistant with source citations
- Hand-over rules to a human, with full context
- Workflow automations connected to your CRM, helpdesk or ERP
- Evaluation set and dashboard to check answer quality
- Access controls so each user only sees what they should
Built with
- OpenAI
- Anthropic Claude
- Llama
- LangChain
- pgvector
- Python
- Node.js
- n8n
What we cover
AI & automation, in detail
Pick one part or the whole set. We scope only what your problem needs.
Assistants and search
- Chat, email and WhatsApp assistants
- Search across documents (RAG)
- Source citations and hand-over to a person
- Voice: speech-to-text and text-to-speech
Agents and automation
- Agents that use your tools through APIs and MCP
- Invoice, form and email extraction
- Workflows across CRM, helpdesk and ERP
- Approval steps where a person must decide
Models
- Model selection and cost comparison
- Fine-tuning on your own examples
- Open models hosted privately
- Evaluation sets that catch regressions
How it runs
From first call to ai & automation in production
You see working software early and can change direction while it is still cheap.
- 01
Find the repeat work
We sit with your team and list the questions and tasks that come back every week. - 02
Prepare the data
We clean and index your documents, and decide what the assistant may and may not touch. - 03
Build and test
We build the assistant and test it against real past questions before anyone outside sees it. - 04
Launch and watch
We launch to a small group first, review answers weekly and widen access when quality holds.
Questions
AI & automation: what people ask
Will the AI make things up?
We limit it to your own sources and show the source with every answer. When it cannot find one, it says so and hands over to a person.
Does our data leave our control?
We can run on your cloud account, use providers that do not train on your data, or host open models privately. We agree this before we start.
Which model do you use?
Whichever fits the job. We often compare two or three on your real questions before choosing.
Planning AI or automation work?
Tell us where things get stuck today. We will reply with a plan, not a pitch.